Longitudinal Position Prediction of Vehicles at Intersections with a Weighted Average Model
Paper in proceeding, 2023
The road user position prediction algorithm Weighted Average Model(WAM) is re-formulated to address one of its main limitations: that WAM can only be applied at geographic locations where data has been collected. This issue is resolved with a change of reference frame, but at the cost of restricting the model to prediction of vehicles' positions along paths. It is additionally shown on real world traffic data that including the curvature of the path a vehicle travels on as input increases WAM's performance. This increase is explained by using the structure of WAM.
prediction methods
weighted average
autonomous vehicles
position prediction
Intelligent vehicles
Author
Angelos Toytziaridis
Chalmers, Electrical Engineering, Systems and control
Paolo Falcone
University of Modena and Reggio Emilia
Jonas Sjöberg
Chalmers, Electrical Engineering, Systems and control
2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
9781665455305 (ISBN)
8th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2023
Nice, France,
Nice, France,
5G for Connected Autonomous Vehicles in Complex Urban Environments
VINNOVA (2018-05005), 2019-04-01 -- 2023-03-31.
Subject Categories
Transport Systems and Logistics
Vehicle Engineering
DOI
10.1109/MT-ITS56129.2023.10241620